Sizing and Characterization of Load Curves of Distribution Transformers Using Clustering and Predictive Machine Learning Models by Pedro Torres-Bermeo, Kevin López-Eugenio, Carolina Del-Valle-Soto, Guillermo Palacios-Navarro, José Varela-Aldás

“…This study applies clustering techniques and predictive models to analyze and predict the behavior of transformer demand, optimize utilization factors, and improve infrastructure planning. …”
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Integrating Model‐Informed Drug Development With AI: A Synergistic Approach to Accelerating Pharmaceutical Innovation by Karthik Raman, Rukmini Kumar, Cynthia J. Musante, Subha Madhavan

“…However, several challenges, including the availability of relevant, labeled, high‐quality datasets, data privacy concerns, model interpretability, and algorithmic bias, must be carefully managed. …”
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Modeling Autonomous Vehicles’ Altruistic Behavior to Human-Driven Vehicles in the Car following Events and Impact Analysis by Wenyun Tang, Le Xu, Jianxiao Ma

“…An extension car following framework with two possible soft optimization targets was proposed in this article to improve the experience of HDV followers with different following strategies by deep deterministic policy gradient (DDPG) algorithm. …”
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Predictive modeling for the adsorptive and photocatalytic removal of phenolic contaminants from water using artificial neural networks by Shahzar Hafeez, Ayesha Ishaq, Azeem Intisar, Tariq Mahmood, Muhammad Imran Din, Ejaz Ahmed, Muhammad Rizwan Tariq, Muhammad Amin Abid

“…To overcome these limitations, the modeling and optimization of water treatment methods is required. …”
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Breaking language barriers with image detection and natural language processing model for English to Spanish translation by Bakhita Salman, Andres Lopez, Nathanielle Delapena

“…Fine-tuning the transformer model parameters, including learning rate scheduling and gradient clipping, further optimized system performance. …”
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Exploring the Current Status of Risk Stratification in Hypertrophic Cardiomyopathy: From Risk Models to Promising Techniques by Alexandros Kasiakogias, Christos Kaskoutis, Christos-Konstantinos Antoniou, Stavros Georgopoulos, Dimitrios Tsiachris, Petros Arsenos, Alexandrina Kouroutzoglou, Dimitrios Klettas, Charalambos Vlachopoulos, Konstantinos Tsioufis, Konstantinos Gatzoulis

“…Some research suggests that integrating electrophysiological studies into traditional risk assessment models may further optimize risk prediction and significantly improve accuracy in detecting high risk patients. …”
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Electric Vehicle Charging Network Planning for Maximizing Charging Service Capability and Operational Efficiency by ZHANG Xinsong; XU Yangyang; YUAN Yue; ZHU Junpeng

“…Firstly, the locations of each EVCS are optimized by genetic algorithm to enhance service capability of the EV charging network. …”
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Research on Maneuvering Motion Prediction for Intelligent Ships Based on LSTM-Multi-Head Attention Model by Dongyu Liu, Xiaopeng Gao, Cong Huo, Wentao Su

“…The results demonstrate that our proposed model significantly improves the accuracy of ship maneuvering predictions compared to standalone LSTM and MHAM algorithms and exhibits superior generalization performance.…”
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Integrating direct observation and environmental DNA data to enhance species distribution models in riverine environments by Luca Carraro

“…When eDNA and direct sampling sites are spatially arranged in an optimized fashion, the highest prediction skill for a fixed total number of sampling sites deployed is reached when both data types are included in the model fitting. …”
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Exploring the Effects of Pre-Processing Techniques on Topic Modeling of an Arabic News Article Data Set by Haya Alangari, Nahlah Algethami

“…This research investigates the impacts of pre-processing techniques on the effectiveness of topic modeling algorithms for Arabic texts, focusing on a comparison between BERTopic, Latent Dirichlet Allocation (LDA), and Non-Negative Matrix Factorization (NMF). …”
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Duty of care, data science, and gambling harm: A scoping review of risk assessment models by Virve Marionneau, Kim Ristolainen, Tomi Roukka

“…Measures to assess the prediction ability of models are not optimal. Industry funding or involvement is prevalent in model development. …”
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Performance Assessment of Undifferenced GPS/Galileo Precise Time Transfer with a Refined Clock Model by Wei Xu, Pengfei Zhang, Lei Wang, Chao Yan, Jian Chen

“…Conventional Global Navigation Satellite System (GNSS) time transfer algorithms typically model receiver clock offsets as white noise for estimation, neglecting the physical characteristics of atomic clocks, which consequently limits the performance of GNSS time transfer. …”
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AC-YOLO: A lightweight ship detection model for SAR images based on YOLO11. by Rui He, Dezhi Han, Xiang Shen, Bing Han, Zhongdai Wu, Xiaohu Huang

“…Experimental results demonstrate that, compared with the baseline YOLO11 model, AC-YOLO reduces parameter count by 30.0% and computational load by 15.6% on the SSDD dataset, with an average precision (AP) improvement of 1.2%; on the HRSID dataset, the AP increases by 1.5%. …”
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State of Health Estimation of Lithium-Ion Batteries Using Fusion Health Indicator by PSO-ELM Model by Jun Chen, Yan Liu, Jun Yong, Cheng Yang, Liqin Yan, Yanping Zheng

“…This optimization enhances the ELM’s performance, addressing instability issues in the standard algorithm. …”
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Dynamic Multibody Modeling of Spherical Roller Bearings with Localized Defects for Large-Scale Rotating Machinery by Luca Giraudo, Luigi Gianpio Di Maggio, Lorenzo Giorio, Cristiana Delprete

“…In conclusion, the developed model represents a promising tool for generating useful datasets for training diagnostic and prognostic algorithms, thereby contributing to the improvement of predictive maintenance strategies in industrial settings. …”
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Research on Feed Forward Adaptive-generalized Model Predictive Control for High-speed Train Automatic Operation by LUO Yuan, YI Jie, BAI Jinlei, ZHANG Zhengfang

“…In view of the characteristics of nonlinearity and time-variability of high-speed train model parameters, this paper proposes a feed forward adaptive-generalized model predictive control (FA-GPC) method for dynamic optimization control of the ATO system along with a constrained multi-object predictive controller. …”
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Development of Advanced Machine Learning Models for Predicting CO₂ Solubility in Brine by Xuejia Du, Ganesh C. Thakur

“…This work demonstrates the robustness and adaptability of ML approaches for modeling complex subsurface conditions, paving the way for optimized carbon sequestration strategies.…”
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MEP-YOLOv5s: Small-Target Detection Model for Unmanned Aerial Vehicle-Captured Images by Shengbang Zhou, Song Zhang, Chuanqi Li, Shutian Liu, Dong Chen

“…This article introduces a drone detection model, MEP-YOLOv5s, which optimizes the Backbone, Neck layer, and C3 module based on YOLOv5s, and combines effective attention mechanisms to improve the training efficiency of the model by replacing the traditional CIoU loss (Complete Intersection over Union) with MPDIoU (Minimum Point Distance-based Intersection over Union) loss. …”
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Development of an AI-Based Image Analysis Model for Verifying Partial Defects in Nuclear Fuel Assemblies by Seulah Kim, Dayun Park, Hyung-Joo Choi, Chulhee Min, Jaejoon Ahn

“…This study aims to increase the accuracy of SNF defect detection by optimizing artificial intelligence (AI)-based classification algorithms. …”
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A study on the risk prediction model for venous thromboembolism in orthopedic inpatients based on machine learning by Bo Zhang, Yumei Qin, Liandi Jiu, Chunming Qin, Jiangbo Wang, Haiqing Zhao

“…Feature analysis and data mining were conducted, and eight different machine learning algorithms were used to build the prediction model. …”
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